The human need for apparel is universal, and drives one of the largest global industries and associated supply chains. Efficiently matching apparel supply with consumer needs and preferences as they relate to function, fit, and style is one of the big challenges of the industry. Typically, consumer transactions for apparel articles or garments are fraught with risk and frequent dissatisfaction due to poor fit. The retail industry aims to serve consumers via physical store-front locations providing opportunity for display, perusal and try-on; however the service offered by such locations is necessarily limited as they consume considerable resources, are expensive to maintain, and are thus limited in number and size, especially outside of urban areas. While the apparel industry produces a huge supply of articles in nearly limitless styles and sizes, in-store inventory is constrained by the limited space available, resulting in less availability of styles and sizes than what is or could be manufactured to supply the broad range of needs. Also, consumers often find store-front locations difficult to get to on their schedule, or inconvenient due to the large amount of time that is required by physical store visits and associated in-store garment try-on.
During the last decade many merchants have begun to offer ever more apparel via the internet; consumers find that online stores typically provide greater range of product and convenience than traditional storefronts. Many online stores gather data about the online consumer and are experimenting with various methods to use table-driven sizing charts or other relatively simplistic methods to recommend sizes or styles, or perhaps to filter the available offerings in the hope that the consumer may more easily find something for their need. However, as of today, all online stores lack an effective method to facilitate actual try-on, thus greatly increasing the transactional risk to both buyer and seller. This in turn has retarded the adoption of the internet for apparel transactions relative to that of other categories such as consumer electronics or other product categories that have easily understood dimensions and do not require an assessment of fit against one's own unique requirements.
Imagine how difficult it would be for a consumer if all clothing stores lacked an actual fitting room. Yet this is the situation a consumer faces when attempting to purchase apparel on-line. What is needed is a way of enabling a consumer to conveniently consider and try-on garments of interest from any location.
The enablement of heretofore-unavailable digital online try-on reduces a consumer's fit uncertainty, and associated transaction risk—because the limitations of physical store access and try-on are removed. Transactions facilitated in this way benefit consumers as well as merchants—through a more effective utilization of the already greater internet product assortment, increased consumer satisfaction with their purchases, greater satisfaction of consumer need leading to greater sales, reduced returns, and ultimately greater loyalty by a consumer to the product brand. Such on-line services will be referred to herein as ONLINE TRY-ONSM services offered by EMBODEE™. ONLINE TRY-ONSM and EMBODEE™ are trademarks owned by MettleWorks, Inc., world-wide rights reserved.
Improved matching between the industry's supply and the consumer's need additionally leads to further subsequent efficiencies, and ultimately accrues to benefit both consumers and merchants, for the following reasons.
As ONLINE TRY-ONSM services would enable a greater percentage of need supplied through internet fulfillment, they in turn would reduce the retail industry's cost of garment inventory and fulfillment through more centralized warehouse operations. This is because physical store-fronts are burdened with greater costs due to retail square footage costs being much greater than warehouse square footage, retail square footage accommodating less inventory than warehouse square footage, and retail labor costs being much greater than warehouse-based fulfillment costs. Articles sold through internet fulfillment also require much less handling than physical storefront locations, thus further reducing costs.
In addition, ONLINE TRY-ONSM services enable reduced consumption of production resources and energy because internet-based fulfillment enables reduced waste because centralized inventory can be more tightly controlled than distributed (in-store) inventory, and because transport to intermediate delivery facilities such as store fronts can be reduced. Thus, industry practices become more sustainable, and fulfillment of consumer's needs becomes more ecologically sound.
Recent innovations in simulating virtual wear articles are summarized in U.S. Pat. No. 7,149,665 B2 entitled SYSTEM AND METHOD FOR SIMULATION OF VIRTUAL WEAR ARTICLES ON VIRTUAL MODELS to Feld, et al. This patent describes conforming a virtual 3D wear article on a virtual 3D model within constraints imposed on the article by a data set representing at least one physical property of the material including material type, texture, weave, threads per unit measure, shear strength, stress, strain, elasticity, yield strength, etc. System architecture includes a vendor station, a user station, and a designer station including a personal computer (PC) that is connected to the vendor stations via the internet. The software—including a 3D real-time rendering engine capable of taking the data associated with the virtual model and wear articles, calculating the fit of the virtual wear model on the virtual model, and displaying the data in a real-time simulated three-dimensional format on a computer screen—is downloaded to the user station from an internet site, and is executed at the user station. Thus, the system described in this patent requires a high-compute power user station for the numerous, arithmetically complex calculations required of real-time fit simulation and subsequent rendering. The patented system requires its software to be developed for every client device that it seeks to support, thus limiting its reach to only directly supported client devices. In addition, it is incompatible with ubiquitous, portable, internet-capable devices such as smart phones, PDAs, mobile handsets, or other any other such device lacking sufficient computational capability to run it, or the availability of this software for it. Finally, it is generally well accepted that a majority of online consumers are reticent or unwilling to download custom software to their client devices because most find it inconvenient, or are fearful of the security risks that software downloaded from the internet can pose. The consequence of this reticence is a sharply reduced reach by any website requiring custom software downloads, and results in online merchants avoiding the use of such technology.
Physically based simulation of cloth is notoriously slow because all methods employ computationally expensive numerical methods. This is an area of research, with speed-ups being pursued by the academic community through the use of parallelization via either central processors or graphics processors. One such example is the paper “Parallel Techniques for Physically-Based Simulation on Multi-Core Processor Architectures”, by Thomaszewski, Pabst, & Blochinger (2008, Computer & Graphics, International Journal of Systems & Applications in Computer Graphics). As papers in the field show, the computational cost for the draping process of a garment correlates directly with the distance that must be travelled between points on the garment and a given body form on to which it is draped, and the time required to allow the garment to achieve a rest state. In their paper the authors report significant speed-ups, however, they still cannot achieve the speeds require for interactive applications such as the one contemplated here. On current generation high-end microprocessors, such as for example an INTEL CORE™ i7, the simulation of cloth and the fit of a dress or shirt on a human body form can take on the order of 30-60 seconds from a flat starting state in order to attain (simulate) the correct shape of the dress or shirt once “worn”, and another 30-60 seconds in order to achieve a highly realistic visualization of the result using advanced visualization techniques such as ray-tracing.
In order for the EMBODEE™ service to achieve the performance required to service, for example, an internet shopper seeking to do an ONLINE TRY-ONSM of a garment, a 1-2 minute wait time would be a hindrance to its use in a shopping context, where speed and convenience are of great importance. Further, if the shopper needs a realistic portrayal via additional perspective views (images), an additional 1-2 minute wait time for each additional image further depicting fit also would clearly not be acceptable. Such unreasonable delay also would make it impossible to offer the shopper a video “vignette” of the garment via a set of streaming images (which would require 10's or 100's of images (frames) for even a short vignette).
Traditional approaches such as those described above have so far involved methods that rely on the computational power available to a given user, such as a PC or other workstation. However, the problem is not only that the best personal computers lack the power needed for an on-demand, real-time ONLINE TRY-ONSM service for the foreseeable future, but also that consumers increasingly desire to access their network based services from not only their personal computers, but also from other devices, including browser enabled phones, for instance. Such devices have 1-2 orders of magnitude less capability than contemporary computers, thus putting universal availability of on-demand try-on further out of reach. Further, an ONLINE TRY-ONSM service as enabled by this invention needs to be made available to not just tens or hundreds of consumers, but to thousands or even hundreds of thousands of potential consumers that are resident on global networks such as the internet today. Such a service needs to operate not on individual or enterprise level scale, but on an internet- or web-scale.
Thus, what is needed is a method to deliver at least two orders of magnitude of speedup, or more, and to make this speedup available to any user, and on any device, regardless of the computational or software resources of their web-enabled device. Getting to greater speedup also facilitates the economic feasibility of delivering an on-demand ONLINE TRY-ONSM service, because less compute time per try-on also means more users can be serviced with a given amount of server resource, and thus with a lower per try-on cost.